WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning

WiMi Releases Next-Generation Quantum Convolutional Neural Network Technology for Multi-Channel Supervised Learning BEIJING, Jan. 05, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...
Kalkine Media

WiMi (NASDAQ:WIMI) Launches Multi-Channel Quantum Convolutional Neural Network for AI Applications

WiMi launched the MC-QCNN, a quantum convolutional neural network capable of processing multi-channel data for applications ...

MicroCloud Hologram Inc. Releases Learnable Quantum Spectral Filter Technology for Hybrid Graph Neural Networks

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...

MicroCloud Hologram stock rises after unveiling quantum spectral filter tech

MicroCloud Hologram’s approach uses a logarithmic encoding method to reduce the number of qubits needed, representing an N-dimensional feature space using just log (N) qubits. The system forms an ...
IEEE

A Generic Algorithm for Position-Orientation Estimation With Microscopic Vision

Abstract: Position and orientation (PO) estimation with microscopic vision is essential for various micromanipulation tasks. Herein, to improve the accuracy and flexibility of PO estimation, a generic ...
IEEE

Edge Enhancement Oriented Graph Convolutional Networks for Point Cloud Segmentation

Abstract: Aiming at the problem of poor edge effect segmentation in point cloud segmentation, which fails to fully utilize the correlation between the local geometric and semantic features of point ...
Frontiers

A Fourier Neural Operator-enhanced parabolic equation framework for highly efficient underwater acoustic field prediction

The parabolic equation (PE) serves as a fundamental methodology for modeling underwater acoustic propagation. The computational efficiency of this approach derives from the far-field approximation of ...
GitHub

Content-Adaptive Non-Local Convolution for Remote Sensing Pansharpening

Abstract: Currently, machine learning-based methods for remote sensing pansharpening have progressed rapidly. However, existing pansharpening methods often do not fully exploit differentiating ...
GitHub

CSformer: Bridging Convolution and Transformer for Compressive Sensing (TIP 2023)

Official Pytorch implementation of "CSformer: Bridging Convolution and Transformer for Compressive Sensing" published in IEEE Transactions on Image Processing (TIP). Checkpoints trained on CoCo ...